jsmall12 commited on
Commit
bfd3013
·
verified ·
1 Parent(s): 3ce2a5d

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +3 -1
README.md CHANGED
@@ -18,6 +18,8 @@ language:
18
 
19
  # DataSci-Coder-14B: Qwen2.5-Coder-14B LoRA Adapter for Data Science
20
 
 
 
21
  A QLoRA fine-tuned adapter for [Qwen2.5-Coder-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct) optimized for data science code generation. The model outputs clean, runnable Python code with zero explanatory text — strictly following code-only instructions.
22
 
23
  ## Key Results
@@ -33,7 +35,7 @@ A QLoRA fine-tuned adapter for [Qwen2.5-Coder-14B-Instruct](https://huggingface.
33
 
34
  - Generates complete, runnable Python code for data science tasks
35
  - Covers statistics, machine learning, deep learning, NLP, time series, and visualization
36
- - Follows instructions very precisely. For example, when told "no explanations," it outputs only code (base model ignores this 40% of the time)
37
  - Handles complex tasks: Bayesian inference, VAEs, GANs, survival analysis, stacking ensembles, SHAP, anomaly detection
38
 
39
  ## Training Details
 
18
 
19
  # DataSci-Coder-14B: Qwen2.5-Coder-14B LoRA Adapter for Data Science
20
 
21
+ [![GitHub](https://img.shields.io/badge/GitHub-Code-black)](https://github.com/jacksonSmall/DataSci-Coder)
22
+
23
  A QLoRA fine-tuned adapter for [Qwen2.5-Coder-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct) optimized for data science code generation. The model outputs clean, runnable Python code with zero explanatory text — strictly following code-only instructions.
24
 
25
  ## Key Results
 
35
 
36
  - Generates complete, runnable Python code for data science tasks
37
  - Covers statistics, machine learning, deep learning, NLP, time series, and visualization
38
+ - Follows instructions precisely when told "no explanations," it outputs only code (base model ignores this 40% of the time)
39
  - Handles complex tasks: Bayesian inference, VAEs, GANs, survival analysis, stacking ensembles, SHAP, anomaly detection
40
 
41
  ## Training Details